Clustering and dendrogram
Sex seems to be the determinng factor in hierarchical clustering. Neither disease status nor ethnicity seem to be clustered in any meaningful manner. Also, one sample seems to have a mismatched ‘sex’ label.
Heatmap
Heatmap with the same clustering. Highly distant groups in columns are separated by sex. Also, only a certain number of most variable CpGs are displayed, a part of which separate the sexes.
PCA
Screeplot
It would take 119 principal components to capture 90% of variance in the data.
Pair plot
Sex by colors. Disease status by shape. The sample with a mismatched ‘sex’ label is visible here too.
PC Heatmap
The heatmap of principal component scores doesn’t reveal much.
PC relation with metadata
Sex
Disease Status
Age
The lighter the point, the higher the age.
Ethnicity
